As Sharon Glotzer gets into the swing of her first term as the Anthony C. Lembke Department Chair of Chemical Engineering at the University of Michigan, we asked her about what she thinks is missing in chemical engineering education.

What needs to change in chemical engineering education to prepare graduates for the future?

There are two things that our students are asking for but don’t currently fit neatly into the curriculum. One, and this could be said for literally any discipline now, is data science.

Data science now drives how we try to make new compounds. If I make my new material this way, it behaves like this. Or if I do something else, it behaves like that. But imagine that you can interrogate millions of trials – or hundreds of millions or billions of trials – and get huge amounts of data. You need data science to find the correlations that will turn those observations into design rules and eventually theories. Data science is the new Wild West.

When I talk to companies, they tell me they are desperate to hire not data scientists to whom they can teach chemical engineering – they want to hire chemical engineers who know data science. And so, that is an exciting opportunity for us.

Another is policy. When you look at major scientific boards, advisory panels or people who testify before congress – it is not uncommon to find they are engineers. They are often chemical engineers, in part because chemical engineering covers everything from fundamental science to very practical implementations of the science – from molecules to manufacturing, we like to say.

And if ever there was a time when we needed more chemical engineers to become involved in science policy, it is now. Our students are excited – they want to get involved. We’re working across the campus to build a pathway for them to combine their chemical engineering studies with science policy.

How can you incorporate data science into an already demanding curriculum?

It may be time to step back and look at the entire chemical engineering curriculum and ask ourselves – are these still the topics that we need to be teaching our undergrads? And if so, are we teaching them the way we should be teaching them, in the most effective ways possible, looking forward? Or, are there ways of packaging our materials in ways that free up time for new topics?

One approach would be to offer data science courses as technical electives. But to me, a much more powerful approach is to integrate data science throughout the curriculum. If they’re so ubiquitous and so important, then it should be possible to integrate data science approaches into core chemical engineering topics such as reaction engineering.

You called the field of data science the new Wild West. How will a chemical engineering department stay current with a field experiencing such rapid growth?

At the University of Michigan, we have two institutes that advance computational approaches to science and engineering – one dedicated to data science itself and the other covering computational science more broadly. Together, they pool all the experts in data and computational science from across the university. Some are creating the tools and techniques of the trade, which are evolving rapidly, while others are more focused on applications – the kinds of questions that data science can answer. These range from climate to self-driving cars to the discovery of new drugs and materials – and everything in between.

Through the Michigan Institute for Data Science and Michigan Institute of Computational Discovery and Engineering, Michigan faculty – including chemical engineering faculty – hold seminars and workshops, summer schools and tutorials, and provide other opportunities for our students to get into data science and computational science as deeply as they wish.

What about connecting students with opportunities in public policy?

As with data science – and this is one of the great things about Michigan – we don’t have to do this alone. The Ford School of Public Policy is a top ten school in public affairs, and through it we have access to experts in public policy and science policy in particular. With their help, we can identify or develop courses best suited to prepare our chemical engineering students to become leading voices for science, energy, the environment, public health, and the many other areas that intersect with chemical engineering.

At Michigan, we pride ourselves not just on being leaders in engineering, but leaders who serve the public good, and the students we attract feel the same way. By working across the campus, I am confident that we can provide not just the education, but also a network that helps our young chemical engineers bring more scientific expertise to the public sphere.

To learn more about Professor Glotzer, including how data science is transforming her own work, see her profile.